Image-Guided Shape-from-Template Using Mesh Inextensibility Constraints

Thuy Tran · Ruochen Chen · Shaifali Parashar
CNRS, École Centrale de Lyon

ICCV 2025

arXiv   |   Supplemental Video |   Presentation

Abstract

Shape-from-Template problem aims to reconstruct 3D object given a template. This repository provides a framework NSfT optimizing shapes using neural networks implemented in PyTorch. The overall pipeline is shown in the figure below.

The object masks can be estimated using SAM 2.

Installation

To install the dependencies, run the following command:

pip install -r requirements.txt

Our code still requires usage of differentiable renderers. We refer to the official documentation of the libraries Nvdiffrast and PyTorch3D for installation instructions.

Usage

To perform 3D reconstruction, you can config the runner using ConfigMyPy. Some config examples reported in our article can be found in configs/ICCV2025.

Then, you can run the following command to start the runner:

python main.py --config_file=configs/your/config/file.yaml --output_path=path/to/save/results/

Citation

Acknowledgements

This work is supported by the project RHINO (ANR-22-CE33-0014-01), a JCJC research grant.

We also thank Φ-SfT and PGSfT for releasing their code and their valuable discussions about the benchmarks.